• KIPS Transactions on Software and Data Engineering
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• v.8 no.10
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• pp.421-426
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• 2019

In this paper, we propose a method to visualize the geometric features of the contact region between proteins in a protein complex. When proteins or ligands are represented as curved surfaces with irregularities, the property that the two surfaces contact each other without intersections is called shape compatibility. Protein-Protein or Protein-Ligand docking researches have shown that shape complementarity, chemical properties, and entropy play an important role in finding contact regions. Usually, after finding a region with high shape complementarity, we can predict the contact region by using residual polarity and hydrophobicity of amino acids belonging to this region. In the research for predicting the contact region, it is necessary to investigate the geometrical features of the contact region in known protein complexes. For this purpose, it is essential to visualize the geometric features of the molecular surface. In this paper, we propose a method to find the contact region, and visualize the geometric features of it as normal vectors and mean curvatures of the protein complex.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.12
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• pp.505-518
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• 2023

3D point cloud semantic segmentation is a computer vision task that involves dividing the point cloud into different objects and regions by predicting the class label of each point. Existing 3D semantic segmentation models have some limitations in performing sufficient fusion of multi-modal features while ensuring both characteristics of 2D visual features extracted from RGB images and 3D geometric features extracted from point cloud. Therefore, in this paper, we propose MMCA-Net, a novel 3D semantic segmentation model using 2D-3D multi-modal features. The proposed model effectively fuses two heterogeneous 2D visual features and 3D geometric features by using an intermediate fusion strategy and a multi-modal cross attention-based fusion operation. Also, the proposed model extracts context-rich 3D geometric features from input point cloud consisting of irregularly distributed points by adopting PTv2 as 3D geometric encoder. In this paper, we conducted both quantitative and qualitative experiments with the benchmark dataset, ScanNetv2 in order to analyze the performance of the proposed model. In terms of the metric mIoU, the proposed model showed a 9.2% performance improvement over the PTv2 model using only 3D geometric features, and a 12.12% performance improvement over the MVPNet model using 2D-3D multi-modal features. As a result, we proved the effectiveness and usefulness of the proposed model.

• Journal of Information Processing Systems
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• v.10 no.4
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• pp.503-522
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• 2014

In the cursive handwriting recognition process, script trajectory segmentation and modeling represent an important task for large or open lexicon context that becomes more complicated in multi-writer applications. In this paper, we will present a developed system of Arabic online handwriting modeling based on graphemes segmentation and the extraction of its geometric features. The main contribution consists of adapting the Fourier descriptors to model the open trajectory of the segmented graphemes. To segment the trajectory of the handwriting, the system proceeds by first detecting its baseline by checking combined geometric and logic conditions. Then, the detected baseline is used as a topologic reference for the extraction of particular points that delimit the graphemes' trajectories. Each segmented grapheme is then represented by a set of relevant geometric features that include the vector of the Fourier descriptors for trajectory shape modeling, normalized metric parameters that model the grapheme dimensions, its position in respect to the baseline, and codes for the description of its associated diacritics.

• The Mathematical Education
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• v.46 no.3
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• pp.245-261
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• 2007

This paper deals with the possible problems which may arise when students learn the names of elementary geometric figures in the languages of Korean, Chinese, English. The names of some simple geometric figures in these languages are analyzed, and a specially designed test was administered to some grade eight students from the three language groups to explore the possible influence of the characteristics of the languages on students' capability in identifying the figures, the way students define the figures, and students' understanding of the inclusive relationship among figures. It was found that the usage of the terms to describe geometric figures may indeed have affected students' understanding of the figures. The names of geometric figures borrowed from those of everyday life objects may cause students to fix on some attributes of the objects which may not be consistent with the definition of the figures. Even when the names of the geometric figures depict the features of the figures, the words used in the naming of the figures may still affect students' understanding of the inclusive relations. If there is discrepancy between the definition of a geometric figure and the features that the name depicts, it may affect students' understanding of the definition of the figure, and if there is inconsistency in the classification of figures, it may affect students' understanding of the inclusive relationship involving those figures. Some implications of the study are then discussed.

• The Journal of the Korea Contents Association
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• v.6 no.6
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• pp.1-8
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• 2006

This paper presents an intelligent pattern matching method that can be used to acquire the reliable calibration data for automatic PCB pattern inspection. The inaccurate calibration data is often acquired by geometric pattern variations and selecting an inappropriate model manual. It makes low the confidence of inspection and also the inspection processing time has been delayed. In this paper, the geometric features of PCB patterns are utilized to calculate the accurate calibration data. An appropriate model is selected automatically based on the geometric features, and then the calibration data to be invariant to the geometric variations(translation, rotation, scaling) is calculated. The method can save the inspection time unnecessary by eliminating the need for manual model selection. As the result, it makes a fast, accurate and reliable inspection of PCB patterns.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.37 no.3
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• pp.209-219
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• 2019

Satellite imagery occurs geometric and radiometric errors due to external environmental factors at the acquired time, which in turn causes false-alarm in change detection. These errors should be eliminated by geometric and radiometric corrections. In this study, we propose a methodology that automatically and simultaneously performs geometric and radiometric corrections by using the SURF (Speeded-Up Robust Feature) algorithm and the mask filter. The MPs (Matching Points), which show invariant properties between multi-temporal imagery, extracted through the SURF algorithm are used for automatic geometric correction. Using the properties of the extracted MPs, PIFs (Pseudo Invariant Features) used for relative radiometric correction are selected. Subsequently, secondary PIFs are extracted by generated mask filters around the selected PIFs. After performing automatic using the extracted MPs, we could confirm that geometric and radiometric errors are eliminated as the result of performing the relative radiometric correction using PIFs in geo-rectified images.

• Current Optics and Photonics
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• v.2 no.2
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• pp.140-146
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• 2018

In this paper, mesoscale optical surface structures are found to possess both geometric and wave optics features. The study reveals that geometric optic analysis cannot correctly predict the experimental results of light transmission or reflection by mesoscale optical structures, and that, for reliable analyses, a hybrid approach incorporating both geometric and wave optic theories should be employed. By analyzing the transmission patterns generated by the mesoscale periodic pyramid prism plates, we show that the wave optic feature is mainly ascribed to the edge diffraction effect and we estimate the relative contributions of the wave optic diffraction effect and the geometric refraction effect to the total scattering field distribution with respect to the relative dimension of the structures.

• Journal of the Korean Mathematical Society
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• v.38 no.5
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• pp.1047-1059
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• 2001

The classical Geometric Brownian motion (GBM) model for the price of a risky asset, from which the huge financial derivatives industry has developed, stipulates that the log returns are iid Gaussian. however, typical log returns data show a distribution with much higher peaks and heavier tails than the Gaussian as well as evidence of strong and persistent dependence. In this paper we describe a simple replacement for GBM, a fractal activity time Geometric Brownian motion (FATGBM) model based on fractal activity time which readily explains these observed features in the data. Consequences of the model are explained, and examples are given to illustrate how the self-similar scaling properties of the activity time check out in practice.

• International Journal of CAD/CAM
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• v.6 no.1
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• pp.173-181
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• 2006

In this paper, an integration framework of Geometric Constraint Solving Engine and AutoCAD is presented, and a dynamic geometric constraint system is introduced. According to inherent orientation features of geometric entities and various Object Snap results of AutoCAD, the' proposed system can automatically construct an under-constrained geometric constraint model during interactive drawing. And then the directed constraint graph in a geometric constraint model is realtime modified in order to produce an optimal constraint solving sequence. Due to the open object-oriented characteristics of AutoCAD, a set of user-defined entities including basic geometric elements and graphics constraint relations are defined through derivation. And the custom-made Object Reactor and Command Reactor are also constructed. Several powerful characteristics are achieved based on these user-defined entities and reactors, including synchronously processing geometric constraint information while saving and opening DWG files, visual constraint relations, and full adaptability to Undo/Redo operations. These characteristics of the proposed system can help the designers more easily manage geometric entities and constraint relations between them.

• Journal of Mechanical Science and Technology
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• v.18 no.12
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• pp.2095-2103
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• 2004

A macro-level CAPP system is proposed to plan the complicated mechanical prismatic parts efficiently. The system creates the efficient machining sequence of the features in a part by analyzing the feature information. Because the planning with the individual features is very complicated, feature groups are formed for effective planning using the nested relations of the features of a part, and special feature groups are determined for sequencing. The process plan is generated based on the sequences of the feature groups and features. When multiple machines are required, efficient machine assignment is performed. A series of heuristic rules are developed to accomplish it.